Skip to content
master
Switch branches/tags
Go to file
Code

README.md

EF_Activities

Hands-on activities associated with the Ecological Forecasting book and graduate class

Book: Dietze, M. 2017. Ecological Forecasting. Princeton University Press https://ecoforecast.org/book

List of activities by Chapter:

Chapter 1: Introduction

  • Exercise 01 - R primer

Chapter 2: From Models to Forecasts

  • Exercise 02 - From models to forecasts

Chapter 3: Data, Large and Small

  • Exercise 03 - Tools for working with data

Chapter 4: Scientific Workflows and the Informatics of Model-Data Fusion

  • Exercise 04 - Pair Coding and Github

Chapter 5: Introduction to Bayes

  • Exercise 05 - JAGS primer

  • Exercise 05B - Bayesian Regression

Chapter 6:Characterizing Uncertainty

  • Chapter 06 - Fitting Uncertainties

  • Chapter 06 - Hierarchical Bayes

Chapter 8: Latent Variables and State-Space Models

  • Exercise 06 - State Space models

Chapter 9: Fusing Data Sources

  • Exercise 07 - Fusing time-series data

Chapter 11: Propagating, Analyzing, and Reducing Uncertainty

  • Chapter 11 - Uncertainty Propagation and Analysis

Chapter 13: Data Assimilation 1: Analytical Methods

  • Exercise 09 - Kalman Filter

Chapter 14: Data Assimilation 2: Monte Carlo Methods

  • Exercise 10 - Particle Filter

Chapter 16: Assessing Model Performance

  • Exercise 11 - Model Assessment

Chapter 17: Projection and Decision Support

  • Exercise 12 - Decision Support

In addition this repository contains the following folders:

  • data - Data files used in the exercises
  • images - Image files embedded in the exercises
  • tutorial - Additional tutorials contributed by previous students

For a list of Git and Github tutorials see http://gist.github.com/Pakillo/63c15c700c9c76fe8032

About

Hands-on activities associated with the Ecological Forecasting book and graduate class

Resources

License

Releases

No releases published

Packages

No packages published